Neighborhood interaction. Nearby sub-structure of proteins and drugs influence each other in triggering the interactions. Hence, besides modeling the individual pair-wise interaction, it is also necessary to model the interaction to the nearby regions. We achieve this through a Convolutional Neural Network (CNN) [1]} layer on top of the interaction map \(\mathbf {I}\) . The intuition is that by applying several order-invariant local convolution filters, interaction to nearby regions can be captured and aggregated. We obtain the output representation \(\mathbf {O}\)  of the input drug-target pair:
\(\mathbf {O} = \mathrm {CNN}(\mathbf {I})\) 
